Evolutionary rough feature selection in gene expression data

An evolutionary rough feature selection algorithm used for classifying microarray gene expression patterns. Since data typically consist of a large number of redundant an initial redundancy reduction of the attributes is done to able faster convergence. Rough set theory is employed to reducts, which represent the minimal sets of nonredundant features capable of discerning between all objects, in a framework. The effectiveness of the algorithm is demonstrated three cancer datasets.